XinCai Xu, Diyang Gu, Shaohua Gao, Lei Sun, Xingyu Lu, Kaiwei Wang, Jian Bai
{"title":"Back to Michelson Interferometer: a precise inspection system for industrial intricate structures defect detection","authors":"XinCai Xu, Diyang Gu, Shaohua Gao, Lei Sun, Xingyu Lu, Kaiwei Wang, Jian Bai","doi":"10.1088/1361-6501/ad1672","DOIUrl":null,"url":null,"abstract":"\n Quality inspection of injection molding products with intricate three-dimensional (3D) structures and diffuse reflection characteristics is a very important procedure in industrial production. However, the current inspection process for these products still heavily relies on visual inspection, which introduces various issues including low efficiency, and missing or false detection. While previous studies have utilized deep-learning methods in conjunction with specific optical sensors and imaging systems to detect defects, the intricate structure of injection molding products and the small magnitude of defects pose significant challenges in defect detection. To address these challenges, this paper proposes an inspection system based on Michelson interferometer capable of detecting and characterizing defects of injection molding products. Notably, by utilizing the modulation of light intensity and an improved image differencing approach, this inspection system is capable of detecting defects with a magnitude as small as 0.1 mm and achieving a remarkable detection accuracy exceeding 93% on self-made datasets without utilizing phase information. The effectiveness of our method is validated by comparison with mainstream deep-learning-based defect detection methods and visual inspection method.","PeriodicalId":18526,"journal":{"name":"Measurement Science and Technology","volume":"23 28","pages":""},"PeriodicalIF":2.7000,"publicationDate":"2023-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Measurement Science and Technology","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1088/1361-6501/ad1672","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
Quality inspection of injection molding products with intricate three-dimensional (3D) structures and diffuse reflection characteristics is a very important procedure in industrial production. However, the current inspection process for these products still heavily relies on visual inspection, which introduces various issues including low efficiency, and missing or false detection. While previous studies have utilized deep-learning methods in conjunction with specific optical sensors and imaging systems to detect defects, the intricate structure of injection molding products and the small magnitude of defects pose significant challenges in defect detection. To address these challenges, this paper proposes an inspection system based on Michelson interferometer capable of detecting and characterizing defects of injection molding products. Notably, by utilizing the modulation of light intensity and an improved image differencing approach, this inspection system is capable of detecting defects with a magnitude as small as 0.1 mm and achieving a remarkable detection accuracy exceeding 93% on self-made datasets without utilizing phase information. The effectiveness of our method is validated by comparison with mainstream deep-learning-based defect detection methods and visual inspection method.
期刊介绍:
Measurement Science and Technology publishes articles on new measurement techniques and associated instrumentation. Papers that describe experiments must represent an advance in measurement science or measurement technique rather than the application of established experimental technique. Bearing in mind the multidisciplinary nature of the journal, authors must provide an introduction to their work that makes clear the novelty, significance, broader relevance of their work in a measurement context and relevance to the readership of Measurement Science and Technology. All submitted articles should contain consideration of the uncertainty, precision and/or accuracy of the measurements presented.
Subject coverage includes the theory, practice and application of measurement in physics, chemistry, engineering and the environmental and life sciences from inception to commercial exploitation. Publications in the journal should emphasize the novelty of reported methods, characterize them and demonstrate their performance using examples or applications.